In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. Michael Leyton's arguments about the nature of perception and cognition are fascinating, exciting, and sure to be controversial. In this investigation of the psychological relationship between shape and time, Leyton argues compellingly that shape is used by the mind to recover the past and as such it forms a basis for memory. He elaborates a system of rules by which the conversion to memory takes place and presents a number of detailed case studies--in perception, linguistics, art, and even political subjugation--that support these rules. Leyton observes that the mind assigns to any shape a causal history explaining how the shape was formed. We cannot help but perceive a deformed can as a dented can. Moreover, by reducing the study of shape to the study of symmetry, he shows that symmetry is crucial to our everyday cognitive processing. Symmetry is the means by which shape is converted into memory. Perception is usually regarded as the recovery of the spatial layout of the environment. Leyton, however, shows that perception is fundamentally the extraction of time from shape. In doing so, he is able to reduce the several areas of computational vision purely to symmetry principles. Examining grammar in linguistics, he argues that a sentence is psychologically represented as a piece of causal history, an archeological relic disinterred by the listener so that the sentence reveals the past. Again through a detailed analysis of art he shows that what the viewer takes to be the experience of a painting is in fact the extraction of time from the shapes of the painting. Finally he highlights crucial aspects of the mind's attempt to recover time in examples of political subjugation.

This book explores the role of causal constraints in science, shifting our attention from causal relations between individual events--the focus of most philosophical treatments of causation—to a broad family of concepts and principles generating constraints on possible change. Yemima Ben-Menahem looks at determinism, locality, stability, symmetry principles, conservation laws, and the principle of least action—causal constraints that serve to distinguish events and processes that our best scientific theories mandate or allow from those they rule out. Ben-Menahem's approach reveals that causation is just as relevant to explaining why certain events fail to occur as it is to explaining events that do occur. She investigates the conceptual differences between, and interrelations of, members of the causal family, thereby clarifying problems at the heart of the philosophy of science. Ben-Menahem argues that the distinction between determinism and stability is pertinent to the philosophy of history and the foundations of statistical mechanics, and that the interplay of determinism and locality is crucial for understanding quantum mechanics. Providing historical perspective, she traces the causal constraints of contemporary science to traditional intuitions about causation, and demonstrates how the teleological appearance of some constraints is explained away in current scientific theories such as quantum mechanics. Causation in Science represents a bold challenge to both causal eliminativism and causal reductionism—the notions that causation has no place in science and that higher-level causal claims are reducible to the causal claims of fundamental physics.

This is a book about the human propensity to think about and experience the world through stories. ‘Why do we have stories?’, ‘How do stories create meaning for us?’, and ‘How is storytelling distinct from other forms of meaning-making?’ are some of the questions that this book seeks to answer. Although these and other related problems have preoccupied linguists, philosophers, sociologists, narratologists, and cognitive scientists for centuries, in Stories, Meaning, and Experience, Yanna Popova takes an original interdisciplinary approach, situating the study of stories within an enactive understanding of human cognition. Enactive approaches to consciousness and cognition foreground the role of interaction in explanations of social understanding, which includes the human practices of telling and reading stories. Such an understanding of narrative makes a decisive break with both text-centred approaches that have dominated structuralist and early cognitivist views of narrative meaning, as well as pragmatic ones that view narrative understanding as a form of linguistic implicature. The intersubjective experience that each narrative both affords and necessitates, the author argues, serves to highlight the active, yet cooperative and communal, nature of human sociality, expressed in the numerous forms of human interaction, of which storytelling is one.

This book is about the interrelationship between nature, semiosis, metarepresentation and (self-)consciousness, and the role played by metarepresentation in evolution. Representations must have emerged via self-organization from non-representational systems (found in physics, chemistry and biology). Major steps have been the evolution of molecules, macromolecules, life, and finally cultural and symbolic systems. Representations and signs are therefore parts of a huge, possibly branching «ladder of beings». Metarepresentations - images representing images, language about language and language-use, thoughts about thoughts - constitute a fascinating theme within such diverse areas of research as philosophy, literature, theology, anthropology and history, neuroscience, psychology and linguistics. The contributions to this book reflect this variety of different, but often interrelated perspectives on metarepresentation. They also exemplify the difficulties of a truly interdisciplinary discourse and show how one may start such a discourse in the field of semiotics, understood as a meta-discipline which brings together all scientific enterprises dealing with human mind and human culture.

The principle of local activity explains the emergence of complex patterns in a homogeneous medium. At first defined in the theory of nonlinear electronic circuits in a mathematically rigorous way, it can be generalized and proven at least for the class of nonlinear reaction-diffusion systems in physics, chemistry, biology, and brain research. Recently, it was realized by memristors for nanoelectronic device applications. In general, the emergence of complex patterns and structures is explained by symmetry breaking in homogeneous media, which is caused by local activity. This book argues that the principle of local activity is really fundamental in science, and can even be identified in quantum cosmology as symmetry breaking of local gauge symmetries generating the complexity of matter and forces in our universe. Applications are considered in economic, financial, and social systems with the emergence of equilibrium states, symmetry breaking at critical points of phase transitions and risky acting at the edge of chaos./a

This book is a remarkable collection of chapters covering a wider range of topics, including unsupervised text mining, anomaly and Intrusion Detection, Self-reconfiguring Robotics, application of Fuzzy Logic to development aid, Design and Optimization, Context-Aware Reasoning, DNA Sequence Assembly and Multilayer Perceptron Networks. The twenty-one chapters present extended results from the SAI Intelligent Systems Conference (IntelliSys) 2015 and have been selected based on high recommendations during IntelliSys 2015 review process. This book presents innovative research and development carried out presently in fields of knowledge representation and reasoning, machine learning, and particularly in intelligent systems in a more broad sense. It provides state - of - the - art intelligent methods and techniques for solving real world problems along with a vision of the future research.

This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 18th annual meeting of the Cognitive Science Society. Papers have been loosely grouped by topic, and an author index is provided in the back. In hopes of facilitating searches of this work, an electronic index on the Internet's World Wide Web is provided. Titles, authors, and summaries of all the papers published here have been placed in an online database which may be freely searched by anyone. You can reach the Web site at: http://www.cse.ucsd.edu/events/cogsci96/proceedings. You may view the table of contents for this volume on the LEA Web site at: http://www.erlbaum.com.

The ability to learn concepts lies at the very core of human cognition, enabling us to efficiently classify, organize, identify, and store complex information. In view of the basic role that concepts play in our everyday physical and mental lives, the fields of cognitive science and psychology face three long standing challenges: discovering the laws that govern concept learning and categorization behavior in organisms, showing how they inform other areas of cognitive research, and describing them with the mathematical systematicity and precision found in the physical sciences. In light of these theoretical and methodological shortcomings, this volume will introduce a set of general mathematical principles for predicting and explaining conceptual behavior. The author’s theory is based on seven fundamental constructs of universal science: invariance, complexity, information, similarity, dissimilarity, pattern, and representation. These constructs are joined by a novel mathematical framework that does not depend on probability theory, and derives key results from conceptual behavior research with other key areas of cognitive research such as pattern perception, similarity assessment, and contextual choice. The result is a unique and systematic unifying foundation for cognitive science in the tradition of classical physics.

Written by an assembly of leading researchers in the field, this volume provides an innovative and non-technical introduction to cognitive science, and the key issues that animate the field.

This book constitutes the refereed proceedings of the Third International Conference, TPNC 2014, held in Granada, Spain, in December 2014. The 22 revised full papers presented in this book were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on nature-inspired models of computation; synthesizing nature by means of computation; nature-inspired materials; and information processing in nature.